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How to value a company – income statement

by jankythoughts2April 28, 2021May 26, 2021Leave a comment

Foreword

This post discusses some common techniques on evaluating the fundamental value of a company by looking at its income statement, for those who are investing, as defined in Investing vs Speculating.

There are, of course, other ways of evaluating the value of a company, which we will cover in other posts. Other posts in this series:

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

How do companies work?

Before we tackle the topic du jour, let’s get down to brass tacks and consider what is even a company? What does a company do? How does it work?

Legally, a company is simply a legal structure where one or more people get together to perform some tasks, generally a business. The company provides a shell to ringfence the business, so that there is a clear separation of concerns between its individual owners, and the business itself. A company, then, can be thought of as a container of a business — though that business may itself be the acquisition of other companies and/or businesses. For example, Berkshire Hathaway, is a holding company, whose main business is to buy other businesses, such as See’s Candies, GEICO, etc. Another interesting example of a “container” company is the SPDR S&P 500 Trust ETF. It is an investment company structured as an exchange traded fund (ETF), with the ticker symbol SPY, and its main business is to buy and hold stocks to track the S&P500 index.

Regardless of the business(es) a company is in, there are a few common aspects shared by all of them:

Companies typically seek commercial profit (we are excluding charities and non-profits in this discussion).
Companies generally have one or more products. Products may be be tangible, like a watch, a machine, etc., or they may be intangible, like a website, an online service, movie rights, etc.
Companies start by taking money from investors (also called shareholders) to invest in producing the product(s).
- Note that this refers only to the initial investors, generally before the company starts trading on the markets.
- If you buy shares of a company with a broker, the company does not generally see a single cent of that money — instead, that money goes to pay off earlier investors, who sold you their shares.
They may also sell bonds or otherwise acquire debt to raise cash to invest in producing the product(s).
Finally, they sell the product(s), ideally at a price higher than the cost of manufacturing the product(s). If they manage to do so, they make a profit.
Profits can then be retained by the company to invest in producing future product(s), or they can be used to pay down debt, or returned to investors via dividends, or to reduce the number of investors/outstanding shares by buying back shares.

Common accounting terms

Even in our simple model of a company above, a lot of interesting terms pop up. Understanding how to read a company’s income statement will require some basic understanding of these terms.

Revenue Gross sales	The total amount of money the company generates from the sales of its product(s). This is almost always the first line of a company’s income statement, so literally the “top line”. Example: A company that sells 1,000 wooden figurine for $20 each, will have revenue of $20,000.
Operating expenses	The expenses that the company incurs through its day to day business operations. These can include costs of customer acquisitions, payroll for its workers (not directly producing the product(s)), research and development, etc. In economics terms, it is essentially the equivalent of “fixed costs”. Example: Our wooden figuring company may have to rent some factory space for its woodcarvers, at, say $6,000, which is its operating expenses. Note that regardless of how many wooden figurines are made or sold, the rent remains at $6,000. For now, we assume the factory is large enough to accommodate any amount of production.
Cost of goods sold	The expenses that the company incurs directly in the production of its product(s). For example, the costs of the materials used to produce the product(s), the payroll for factory workers, etc. In economics terms, it is essentially the equivalent of “marginal costs”. Example: Let’s say that to produce a single figurine, the company has to buy a block of wood for $5, and pay a woodcarver $4 to carve the wood into a figurine. So the cost to produce each figurine is $9. With our sales of 1,000 figurines, our cost of goods sold is $9,000. Note that cost of goods sold is directly proportional to the amount of wooden figurines sold. The more figurines sold, the more our cost of goods will rise.
Gross income Gross margin Gross profit	This is the the difference between “revenue” and “cost of goods sold”. Gross income tells you how much money the company generates simply from producing and selling its product(s). Example: In our example, our company will have gross income = revenue ($20,000) – cost of goods sold ($9,000) = $11,000. Notice that gross income relates directly to our marginal profitability — if gross income is negative, no amount of additional sales will save our company from eventual bankruptcy! In fact, if gross income is negative, then the company must be selling each unit of product at a loss. So the more units the company sells, the more money the company loses! Imagine a business that sells $1 notes for 50cents. That company has negative gross income and will go bankrupt eventually — the more “products” it sells, the faster it goes bankrupt!
Operating income Operating profit	This is the difference between “gross income” and “operating expenses”. Operating income tells you how much money the company generates from its operations. Example: Continuing with our wooden figurine company, its operating income = gross income ($11,000) – operating expenses ($6,000) = $5,000. Since operating expenses are (mostly) independent of how many product(s) we sell, operating income is basically just what’s left over, after our gross income is used to pay for “overheads” like rent, utilities, legal fees, administrative fees, etc. Note how a company that has negative operating income, but very high gross income, may actually be in good shape! It may simply be a new company, that needs to ramp up sales. With more sales, gross income will quickly overtake operating expenses and thus lead to high, positive operating income.
Non-operating income	Any income that the company receives that is not due to its primary business. Example: Our company has a interest-bearing savings account which paid the company interest, for a total non-operating income of $1,000. Note that for some investment companies, some types of interests and dividends from its assets may be considered revenue!
Non-operating expenses	Any expense that the company incurs that is not due to its primary business. Example: Our company once sold a defective wooden figurine to a customer, who sued and won a judgement of $2,000, which would fall under non-operating expenses.
Income before tax	This is the total amount of profit the company makes before paying its taxes. This is simply “operating income” + “non-operating income” – “non-operating expenses”. Example: Our company has an income before tax = operating income ($5,000) + non-operating income ($1,000) – non-operating expenses ($2,000) = $4,000.
Net income	This is the income of the company, after paying (or setting aside money for) any taxes it may owe. Example: Our company has a tax rate of 20%, which works out to total taxes = income ($4,000) * 20% = $800. Therefore, its net income = income ($4,000) – taxes ($800) = $3,200.
Normalized income before tax	Normalized income tries to remove the “noise” of regular income by removing one off expenses or gains. The goal here is to smooth out fluctuations of our income statements, so that long term performance of the business(es) can be easier to discern. Example: Our company has some non-operating expenses and income: Interest from its savings account of $1,000 Payment for a lawsuit it lost for $2,000 Since our company will likely continue maintaining its savings account, but will (hopefully) not be sued (and lose!) on a regular basis, the $1,000 can be considered recurring income, while the $2,000 payout can be considered a one off expense. Therefore, our normalized income before tax = income before tax ($4,000) + one off expenses ($2,000) – one off income ($0) = $6,000. Warning: Be careful about how companies classify “one off” expenses and income. It is easy to make the income statement look better than it is, if we classify every expense as “one off” and every source of income as “recurring”! The astute investor should recognize if the level of “one off” expenses remains stubbornly high over long periods of time. Such persistently high “one off” expenses, may really just be a real cost of business that management is misclassifying. Similarly, if certain sources of income fluctuate greatly over time, then maybe those incomes are really one off!
Normalized income after tax	This is just normalized income before tax, with the taxes due removed. For example: In our example, normalized income after tax = normalized income before tax ($6,000) – taxes ($800) = $5,200. Notice how the tax rate is based on actual income before tax, and not normalized income before tax! This is another reason why one should be really careful about how some incomes and expenses should or should be classified as “one off”.
Weighted average shares outstanding	Over the course of a reporting period, a company may issue shares to its employees, executives or board members as a form of compensation for their services. At the same time, a company may choose to buy back some of its outstanding shares on the open market with excess cash it may generate. Because of these, the number of shares outstanding of a company is rarely static — it typically changes slightly over time. The weighted average shares is just the sum of number of shares outstanding over the reporting period, weighted by the fraction of the period those shares are actually outstanding. Example: At the start of a reporting period, our company has 1,000 shares outstanding. One-quarter of the way through the reporting period, our company buys back 200 shares. Half way through the same reporting period, our company issues 400 shares to its employees. So, for the first quarter of the period, there are 1,000 shares outstanding. For the next quarter, there are 800 shares outstanding. And for the remaining half, 1,200 shares outstanding. Weighted average shares outstanding = 1,000 * 0.25 + 800 * 0.25 + 1,200 * 0.5 = 1,050 shares.
Diluted weighted average shares outstanding	In addition to issuing new shares, a company may also issue warrants (or options) on its shares. These directly issued warrants/options give the bearer the right, but not the obligation, to buy more shares directly from the company at a certain price — the strike price. If and when the bearer exercises these warrants/options, the company is obligated to create new shares out of thin air, and sell them to the bearer at that strike price. Once these warrants/options are issued, the company has no control on when the bearer may decide to exercise them. However, until the bearer actually exercises them, these warrants/options are not actual shares — they have no voting rights and they do not partake in any financial gains of the company. In order to show the potential effects of these warrants/options on the number of shares outstanding, we can look at diluted weighted average shares outstanding. This is simply the weighted average shares outstanding, increased by the number of shares that the company would be obligated to issue if all outstanding warrants/options directly issued by the company are exercised. Example: In addition to the outstanding shares, our company has issued 2 warrants, each for the purchase of 100 shares (200 shares total), to the CEO. Diluted weighted average shares outstanding = 1,050 + 2 * 100 = 1,250 shares.
Basic earnings per share Primary earnings per share	“Basic” and “Primary” means non-diluted in this case, so basic earnings per share simply refers to the ratio of net income, over the weighted average shares outstanding. Example: For our company, we have net income of $3,200, and weighted average shares outstanding of 1,050. Therefore, the basic earnings per share = $3,200 / 1,050 = ~$3.05 / share.
Diluted earnings per share	We can also look at earnings per share on a fully diluted basis, in which case, we’ll use the diluted weighted average shares outstanding as the denominator of the ratio. Example: For our company, we have net income of $3,200, and diluted weighted average shares outstanding of 1,250. Therefore, the basic earnings per share = $3,200 / 1,250 = $2.56 / share. Notice how the dilutive effects of the 2 warrants issued to the CEO dramatically reduced our earnings per share! While directly issued warrants/options don’t represent actual shares until they are exercised, they still represent potential claims on the future profits of the company and should not be overlooked.
Basic normalized earnings per share	We can also consider earnings per share on normalized earnings to smooth out one off expenses and income. Example: For our company, we have normalized income after tax of $5,200, and weighted average shares outstanding of 1,050. Therefore, the basic earnings per share = $5,200 / 1,050 = ~$4.95 / share.
Diluted normalized earnings per share	Finally, we can consider earnings per share with normalized earnings, on a fully diluted basis. Example: For our company, we have normalized income after tax of $5,200, and diluted weighted average shares outstanding of 1,250. Therefore, the basic earnings per share = $5,200 / 1,250 = $4.16 / share.

Valuation models

When considering the income statement, there are a few natural ratios, or valuation models, that we can use. Here we discuss the more common ones, using our example company above. For reference, we’ll assume that each share of our example company is selling for $100 right now.

Price / Earnings (P/E) ratio	The most popular ratio, the P/E ratio is available on almost every major financial research platform and provides a quick and easy reference number that is reasonably comparable across multiple industries. The P/E ratio can be computed as: Price per share / Earnings per share. In general, “P/E ratio” refers to “basic P/E ratio”, that is, price per share divided by basic earnings per share. Be very careful though! Just as there are 4 common variations of “earnings per share”, there are also 4 common variations of P/E ratios. Even though most sources quote “basic P/E ratio”, that is not true of every source! More egregiously, some sources quote different flavors of P/E ratios across different companies they report on, taking the confusion to a whole new level. To make things even more confusing, some sources make a distinction between “forward P/E ratio” and “trailing P/E ratio”. The former is computed using earnings projection for the future, while the latter is computed using realized, historical earnings. Looking at the P/E ratio is simply answering the question “how much do I pay, for $1 of net income?” — A P/E ratio of 30, means you pay $30 for every $1 of net income the company generates. Example: For our company, the P/E ratio is simply 100 / 3.05 = ~32.8. The diluted P/E ratio is 100 / 2.56 =~ 39.1. The normalized P/E ratio is 100 / 4.95 = ~20.2. The diluted normalized P/E ratio is 100 / 4.16 = ~24.0. Notice how dilution and normalization of earnings dramatically changes our computed “P/E ratio”. When to use P/E ratio: P/E ratio is generally comparable across companies in the same sector/industry. For example, comparing the P/E ratios of 2 companies manufacturing the same (or similar) Widget can give you an idea of which one may be a better value to invest in. Be careful when comparing P/E ratios of an established company and a startup! As discussed above, net income is affected more by sales and less by fixed costs when a company is more mature, while net income is affected more by fixed costs and less by sales when a company is young. At the same time, gross income tends to improve as companies ramp up their sales, due to economies of scale, which further exacerbates this issue. When comparing across sectors/industries, caution also needs to be exercised. Due to the rules of accounting, and the nature of different businesses, P/E ratios don’t tend to be comparable across sectors/industries. For example, a high growth industry may naturally support higher P/E ratios, because investors are looking towards the future, where higher income will naturally deflate the P/E ratio. However, a low growth industry will likely have lower P/E ratios, because the future is likely very similar to the recent past. The most egregious examples where P/E ratios don’t even work are generally due to accounting rules — Consider a real estate investment trust (REIT) that owns commercial buildings and rents them out. A cost of business would be the cost of the buildings themselves — buildings age with time and eventually need to be rebuilt/replaced. However, the lifespan of a building depends on the weather, the type of building, seismic activities in the region, whether maintenance is properly done on the building, and a myriad of other issues. Clearly there is no easy way to quantify all of these to arrive at a reasonable “expense” line item. Yet REITs need a way to be able to deduct this very real cost from their income — no company wants to pay taxes on “profits” that it did not really earn, because that “profit” is really just a deferred “cost of goods sold”. The accounting rules that are used to allow REITs to recognize the very real cost of building depreciation tends to be overly generous when buildings are properly taken care of — in general, buildings last longer than the rules assume, so actual amortized cost is usually lower than what the accounting rules assume. This results in income statements that look worse than they really are, because the “operating expense” of “depreciation” distorts the picture significantly. In situations like this, another measure other than the P/E ratio can be used to evaluate the company’s worth — REITs tend to be valued using their cash flow statements instead of their income statements, a topic we’ll discuss in a future post. For now, it is important to note that almost all major companies have some amount of factory equipment, buildings and/or other assets that depreciate over time. The accounting rules clearly is not able to quantify the actual depreciation rates in all cases. Therefore, the take away is this — the higher the “depreciation and amortization” line items on a company’s income statement are, the more likely they are distorting the income (and thus P/E ratio) of the company.
Price / Sales (P/S) ratio	Another common ratio used to evaluate companies, the P/S ratio is generally seen as “cleaner”, because it avoids completely the distorting effects of how accounting rules affect different sectors/industries. The P/S ratio can be computed as: Market capitalization / Revenue. Where “market capitalization” is just price per share multiplied by weighted average shares outstanding. Notice how this metric completely bypasses “normalization” of income, because we are not considering expenses. Also, this metric is almost always used in the basic form — P/S ratio is almost never computed with diluted weighted average shares outstanding. Looking at the P/S ratio allows us to answer the question, “how much am I paying, for each dollar of sales?” — A P/S ratio of 3, means that for every dollar of sales, the investor is paying $3. Example: For our company, the P/S ratio is simply (100 * 1,050) / 20,000 = 5.25. When to use P/S ratio: Remember our example above, about comparing a mature company’s P/E ratio against that of a startup? We said that this comparison doesn’t work, because the startup’s income is unfairly dominated by its fixed costs, which will become less of an issue once the company ramps up it sales. The P/S ratio does not have this issue! If we are confident that, at steady state, the startup will have a similar marginal gross income (that is, gross income per unit of product sold), and that the startup will have a similar operating expense as the mature company, then one easy way to compare the operating metrics of these 2 companies right now, would be to consider their P/S ratios. Next, let’s consider those sectors/industries that are highly cyclical, such as heavy industrial manufacturing. Companies in these sectors/industries tend to require high levels of investment in factories and equipment every few years. If you look at the net income of these companies, you’ll notice that they are highly cyclical — there will be long periods of low (or even negative) net income, which coincides with periods when the companies are building out new factories and equipment. These will then be followed by long periods of much higher net income, when the build out is at a lull. Due to this need for cyclical investment in their businesses, the P/E ratios of these companies tend to also fluctuate significantly over time, and thus are not reliable indicators of the companies’ health. Instead, the P/S ratio may be more suitable, because it takes away the distorting effects of the cyclical costs of investing in the business. There are some caveats to the P/S ratio, of course. Unlike the P/E ratio, P/S ratio does not take into account costs of business, which while liberating in some cases, can be highly misleading in others. For example, a software company may be able to earn a high operating margin (the ratio of its revenue that eventually translates into profits), but a retail store may not! In general, the same dollar of sales in different sectors/industries may not translate into the same profit, which dramatically curtails the use of P/S ratio comparisons across sectors/industries. Similarly, a company that is mostly funded by debt will have much higher debt servicing costs than another company that is mostly funded by equity. In the former case, after paying the interest on the debt, the company will likely have much less profits left for shareholders compared to the latter case. Finally, like the P/E ratio, the P/S ratio does not take into account growth of the company. A company that is rapidly growing, may command a higher P/S (and P/E) ratio, because investors are looking towards the future, where highly sales will naturally bring both ratios down.
Price / Earnings-to-Growth (PEG) ratio	To account for potential future growth, the P/E ratio is sometimes augmented by normalizing it against projected (or historical) earnings growth. This gives rise to the PEG ratio. The PEG ratio can be computed as: (Price per share / Earnings per share) / Earnings per share growth = P/E ratio / Earnings per share growth Where “earnings per share growth” can be either forward (i.e: projected) or trailing (i.e: from historical data), giving rise to “foward PEG ratio” and “trailing PEG ratio”. Note that in both cases, the basic (i.e: non-diluted) version of P/E and earnings per share are used. The PEG ratio does not conform to any reasonably English question that we can ask. Instead, it is a unitless value that just gives an indication of how expensive a stock is, with regards to both earnings and growth. Example: Recall that the basic P/E ratio of our company is ~32.8, and it has earnings per share of $3.05. Let’s assume that the previous year, the earnings per share of our company was $2.50, and that in the next year, the earnings per share of our company is projected to be $3.50. Trailing earnings per share growth = (3.05 / 2.50) – 1 = 22% Future earnings per share growth = (3.5 / 3.05) – 1 = ~15% Trailing PEG ratio = 32.8 / 22 = ~1.49 Future PEG ratio = 32.8 / 15 = ~2.19 Clearly, our company was a better value PEG ratio-wise, last year, than this year! When to use PEG ratio: The PEG ratio gives an idea of how expensive a stock is, compared to its rate of growth. This may be useful as a complement to any other valuation methods which did not take into account growth of the company, such as the P/E ratio, or the P/S ratio. The smaller the PEG ratio of a stock, the more attractive it is with regards to earnings growth. Therefore, when comparing two companies in the same sector/industry, but with dramatically different growth profiles, the PEG ratio may be a useful measure to take into consideration.
Enterprise value / Earnings before interest, taxes, depreciation and amortization (EV/EBITDA) ratio AKA Enterprise multiple	Now, let’s take a step back, and consider a company from another view point — that of a potential acquirer, say, a competitor. What would the competitor use to quickly evaluate whether our company is worth buying? First, let’s consider what the competitor would care about. The competitor likely wouldn’t care very much about the interest expense that the company pays — assuming the competitor has the deep pockets to buy out our company, it may very well also have the ability to pay off the company’s debts, which will nullify the interest fees. After all, how a company finances its operations (through debt or equity) is fungible as money is fungible. The competitor likely cares about taxes paid, but the consideration is more complex than just what our company pays in taxes. Remember that taxes is on profits, which is affected by expenses such as interest, which we’ve already discarded. Separately, combining two companies may reduce operating expense (remember that operating expenses are those expenses that tend not to scale with units of product sold — so some of these expenses can be removed when the companies merge), which then increases profits and taxes. In general, the final effect of taxes on the combined company is not as simple as just adding up their individual tax bills. So we can probably exclude taxes too, for now. The competitor also probably doesn’t care about our company’s accounting of depreciation and amortization effects either. Accounting rules tend to reset depreciation and amortization line items every time an asset changes ownership, which then changes the buyer’s accounting of depreciation and amortization. And finally, any cash that our company owns, is irrelevant — using cash to buy cash is just silly, so we should ignore them. If our company has $1,000 in cash, the competitor will have to pony up an additional $1,000 to buy our company, but this $1,000 on both sides of the ledger will cancel out. So, what is the actual cost to our competitor for acquiring our company? They’ll need to pay off all existing shareholders at the current share price (share price * outstanding shares = market capitalization), they’ll need to pay off all debts, and they can ignore the cash balance on our company, because cash is just fungible. This gives us a definition of enterprise value: Enterprise value (EV) = market capitalization + debt – cash and cash equivalents At the same time, by paying “enterprise value”, our competitor is getting a stream of earnings that ignores interest payments, taxes, depreciation and amortization, or “earnings before interest, taxes, depreciation and amortization” (EBITDA). So the ratio they care about is EV/EBITDA. Example: For our company, market capitalization = 100 * 1,050 = $105,000. We have no debt, and $1,000 in cash, so enterprise value = $105,000 + $0 – $1,000 = $104,000. $104,000 is how much it would cost, for a competitor to acquire our company outright. And by paying this $104,000, our competitor would get value in the form of EBITDA, equal to = net income ($3,200) + taxes ($800) + interest payment ($0) + depreciation/amortization ($0)= $4,000. And the enterprise multiple = 104,000 / 4,000 = 26. When to use enterprise multiple: Enterprise multiple is mostly only useful for considering the unlevered (i.e: no debt, fully equity funded) operations of a company, and without considering such costs as taxes, depreciation and amortization, which tend to change dramatically after a company is merged with a larger entity. After the merger, the combined company can then decide to re-lever (i.e: get into debt) its operations, but that is a future consideration. For the personal investor, enterprise multiple isn’t particularly interesting, except where the company may be a candidate for acquisition. For example, sectors/industries tend to consolidate as they mature, where larger companies buy out their smaller competitors. In these cases, it may be useful to consider how the larger companies may value their competitors. After all, if you can buy a company that is primed for acquisition at a good enterprise multiple, there is a good chance that one of its larger competitor will then buy the company from you in future at a higher enterprise multiple, ensuring a good profit! (1)

How much is too much?

So, now that we have a “brief” overview of the different metrics that can be used to evaluate a company, based on its income statement, the next obvious question is, what yardstick do we use?

Is a P/E ratio of 10 good? How about 30? 100? Or may be a P/S ratio of 2? 3? 5?

The short answer, is that there is no real yardstick that works across all companies. As discussed above, P/E ratios tend to mellow (come down) as companies mature. They are also affected by various other issues like accounting and the cyclical nature of some sectors/industries. P/S ratio, PEG ratio and the enterprise multiple all have their own issues as well.

For simplicity, going forward, I’ll only consider the P/E ratio, with the assumption that somehow, all the distorting non-operations related issues are ironed out and accounted for. This argument then generalizes better across the different valuation metrics, and we are considering only the raw, operational characteristics of the company. (2)

How much do we want to pay?

So, given our new “perfect P/E ratio”, what yardstick should we use? This is where price discovery comes in.

Remember that the P/E ratio is simply how much we want to pay, for each dollar of earning. Clearly, that is a decision that is dependent on the individual.

For someone who has the option of investing either in a public company on the open market or investing in a private company at a fixed valuation, then the price they would be willing to pay for the public company would be dependent on the valuation of the private company — if the private company is selling for a P/E of 20, then it makes very little sense(3) to invest in the public company at a valuation much higher than a P/E of around 20.

However, for someone else who has only the option of investing in the same public company, or putting their money in a savings account earning 1% interest (i.e: paying $100 to earn $1, or “P/E ratio” of 100), then they may be willing to pay substantially more.

The final clearing price of the company’s stock, will then be a reflection of all opportunities available to all investors, such that all capital is properly deployed across all assets (in this case, the public company, the private company, and the savings account). The final result may very well be that the first investor deploys their capital entirely into the private company, while the second investor deploys their capital into the public company at a P/E ratio of 100.

Yes, this means that the private investor, at least nominally, stands a higher chance of coming out ahead in the long run, but that is not a consideration for price discovery, but a reflection of the intrinsic inefficiencies of the markets (both public and private).

So, to put it simply, for the rational, purely financial(4) investor, and assuming a “perfect P/E ratio” can be defined, then the highest P/E ratio they should pay, should be the P/E ratio of the next best investment available to them.

How certain are you?

In a perfect world, where you can be certain of your projections of a company’s growth, where you can define a “perfect P/E ratio”, etc., choosing the “next best” P/E ratio to pay is the rational thing to do. However, the world is hardly perfect, and uncertainty abounds.

For example, how confident are you in the projections that management makes for the company’s forward progress? Is management likely to overestimate? What are their incentives? Also, even if management is perfect at estimating their own company’s operations, how good are they are estimating the operations of competitors? What about future competitors that don’t even exist right now?

In reality, companies rarely perform according to their projections, and events in the future may dramatically diverge from our projections. Because of this, we need to build some amount of “margin of safety” into our assumptions.

For example, in the case of our public investor, choosing between investing in a public company and a savings account, they need to recognize 2 important facts:

The savings account is guaranteed by the FDIC, so unless they have more than the FDIC insurance limits in the account, or the FDIC itself goes bankrupt, they are very unlikely to lose money. Therefore, the “capital” “invested” in a savings account is generally considered safe.
Any capital invested in the public company has no such protections. An unforeseen event, say a once-in-a-hundred-years pandemic, may occur, causing irreparable harm to the company’s business and forcing it to shutdown, leaving shareholders with nothing.

So when choosing between investments, we also need to consider the potential risks in the investments, not just of the risk of returns (i.e: the probability that returns in future will match returns in the past), but also the risk of loss (i.e: the probability that we won’t even be able to recoup our initial investments).

It is with this in mind that we define a “margin of safety” — when considering between a “safe” “investment” like a 1% yielding savings account (implicit “P/E ratio” of 100), and a public company, we may very well decide that the public company should only command, at most, a P/E ratio of 17, because of all the inherent future unknowns that we need to account for. This gives our company a nominal yield of around 6% (1 / 17 = ~0.059 = 5.9%), for a “margin of safety” of 4.9% (5.9 – 1 = 4.9%).

This “margin of safety”, is sometimes also called the “equity risk premium”. It is, roughly speaking, the additional yield that investors demand from equity investments, over risk-free investments due to the inherent riskiness of equity investments.

Obviously, different investors have different appetites for risk — some investors may demand a 5% equity risk premium (i.e: stocks should yield at least 5% more than risk free investments), while others may demand much lower or higher premiums.

The combined preferences of all investors across the whole market, for all possible investment assets will interact to settle on a clearing price for all our investments.

Footnotes

Note that this is delving into speculation territory, since we are depending on someone else valuing the company higher than we do, instead of just making a profit purely on the operations of the company.
Obviously, this is a departure from reality — such a measure that properly takes into account all the myriad of issues is simply not possible. The assumption here is that the reader will consider all the relevant metrics (PEG ratio for growth companies, P/S ratio for startups, etc.), and come up with a personal composite that they believe in.
This assumes our investor does not care for diversification, which is obviously not traditional and generally not advised.
“Purely financial” here meaning that the only consideration is financial — the investor does not care about other things like sentimentality (I just like the stock), environmental concerns (I like green stocks), etc.

How Does Trade Execution Work

by jankythoughts2April 16, 2021April 24, 2021Leave a comment

Foreword

This post discusses what happens from the time when you send an order, to the time when your order is either rejected, cancelled or executed.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Definitions

Instrument	Any tradable thing, generally interchangeable with “security”.
Lot	Usually means 100 shares of a particular stock. Some stocks, like BRK-A are so expensive that a “lot” of that stock is just 1.
Odd lot	Any number of shares of a stock less than a lot. For example, 50 shares of AAPL is an odd lot.
Order	A firm commitment to trade an instrument at a certain price, either buying or selling. An order can be cancelled, but until it is, the issuer of the order must stand ready to fulfill their promise to buy or sell.
Flow	A stream of orders, sometimes also used for a stream of IoIs.
Book	The totality of all orders that an entity knows about, for a particular instrument. For example, NASDAQ may have a book for GOOG that looks like: Bids: 100shares@$100, 200shares@$90 Asks: 100shares@$101, 300shares@$110
Top of Book (ToB)	The best bid and ask of a book. In the example above, the ToB would be: Best bid: 100shares@$100 Best ask: 100shares@$101
Trade	Also called an “execution”. A trade happens when 2 orders, one buying and one selling, agree upon a price and quantity for an instrument. This results in money going from the buyer to the seller, and the instrument going from the seller to the buyer.
Order matching	The act of finding 2 orders to produce a trade. In our example above, no 2 orders can match, because the best bid is below the best asking price. However, if a new order comes in to buy 50shares@101, then this order can be matched with our best ask, to produce a trade 50shares@$101 After this trade, our ToB would be: Best bid: 100shares@$100 Best ask: 50shares@$101
Market data	A (maybe real time, maybe delayed) stream of information about the trades and the state of the books of an exchange.
Venue AKA trading venue	A venue refers to either an exchange or alternative trading system, where traders can send their orders to get routed to another venue, or to be executed.
Exchange AKA lit exchange AKA lit venue	A trading venue that publishes market data publicly, e.g: NASDAQ, NYSE, Amex, etc.
Dark pool AKA Alternative Trading System (ATS)	A trading venue that does not publish market data publicly, e.g: Sigma X, CrossFinder, MS SORT, etc. They are not always an “exchange” — an “exchange” implies a book and order matching — dark pools may not have a book and may not match orders, they may trade against incoming orders using their own portfolio.
Protected quotes AKA National Best Bid and Offer (NBBO)	This is the ToB of all lit exchanges put together. For example, if NASDAQ has these quotes for MSFT: Bids: 100@$50, 200@$49 Asks: 300@$52, 400@$53 and NYSE has these quotes for MSFT: Bids: 500@$49, 600@$48 Asks: 700@$51, 800@$52 Then the NBBO is: Best bid: 100@$50 Best ask: 700@$51 Note that odd lots are generally ignored for the purpose of computing the NBBO. i.e: Odd lots are generally not protected, even if they are the best bid or ask.
NMS	National Market System, created by Investment Act of 1933. NMS is a rule which says that any order that is executed, must execute at a price within NBBO (inclusive). There are some exceptions, but these typically don’t apply to retail orders.
Regular trading hours (RTH)	Between 9.30am and 4pm Eastern time on a trading day. This is the period of time when the market is said to be “open”, and starts with the opening auction at 9.30am, and ends shortly after the closing auction around 4pm.
After hours	Any time other than RTH.
Broker	An entity that takes an order and figures out where to send it so that it can get matched and executed.
Dealer	An entity that takes an order, and trades against it (i.e: the dealer is the counterparty of the order creator).
Broker/Dealer (BD)	Most brokers are also dealers, and vice versa. Because of this, brokers and dealers are collectively known as brokers/dealers or BDs for short.
Market maker (MM)	An entity that is mandated by SEC/FINRA rules to always keep a bid and ask up for the instrument that it is market making for, on a particular exchange. Note that a market maker for FB on NASDAQ may not be a market maker for FB on NYSE, etc.
Wholesale market maker (WMM)	Really a BD, a WMM is an entity that accepts orders from retail brokers, and either a) Figures out where to route that order so that it can be matched and executed, OR b) Trades against the order using their own portfolio, OR c) Holds the order in their own book for matching against future orders.
Informed	An adjective to describe either an entity, order or flow. An informed entity, order or flow is someone or something that has an edge. In general, this edge involves some non-trivial understanding of the system and/or the macro and/or micro environment(s). Usually, “informed” is applied with a very short time horizon. For example, an order is informed if within a few milliseconds to seconds of the order being sent, the price of the instrument moves upwards. Also called “toxic”. (1)
Uninformed (1)	An adjective to describe either an entity, order or flow. An entity, order or flow that is uninformed is, well, not informed. Typically synonymous to “retail orders/traders”, it is also generally applicable to more sophisticated entities, such as hedge funds, if they are not trying to optimize for very short term (milliseconds to seconds) time horizons.

Basics

There are 10+ lit exchanges in the US for equities, several more for options, futures, etc. In general, to be called an “exchange” requires being subject to stringent regulatory rules set by the SEC, a Federal government agency. Exchanges, in turn, are part of FINRA, which is a self-regulatory body consisting of exchanges and large brokerages. Together, SEC and FINRA set the rules that govern all equities trading in the USA.

A trade can happen as long as all the rules that SEC/FINRA impose are met. The rules which generally apply are:

NMS is enforced during RTH and so all trades must occur within NBBO (inclusive).
- There are exceptions to this rule, such as for large orders (block trades), corrective trades (busts, corrects), etc.
During RTH, prices cannot move by too much within a 5-minute period. The bands are defined using an algorithm the SEC dictated.
- Orders which are outside the band must be modified to comply or rejected by the broker.
- Even if trades are within the bands, if volatility is too high as judged by various parties (SEC, FINRA, exchanges, etc.), trading in a particular stock can be halted.
During RTH, circuit breakers are in effect — if the price of S&P500 declines by too much, the entire market is halted for defined periods of time, up to an including an early end of the trading day.

Order handling

Only licensed BDs are allowed to connect directly to exchanges. As part of maintaining that license, BDs agree to a shared responsibility to “maintain orderly markets”. What this means, is that all rules that the SEC/FINRA impose, must be adhered to by all BDs. If an order which is in breach of the rules is received by a BD, they are responsible for either modifying the order so that it is compliant, or rejecting the order. Any BD who forwards (routes) a non-compliant order to another BD or exchange, may find themselves being disciplined by the SEC/FINRA.

Because there are so many rules to pay attention to just to validate an order, most BDs don’t actually connect to the exchanges directly. Instead, they have contracts with other BDs, such that the original BD is allowed to send some types of non-compliant orders to the second BD, and the second BD assumes the responsibility of validating and possibly rejecting those orders. In effect, our original BD has its own BD. The original BD, the introducing BD, will forward any orders they receive to the second BD, the executing BD. The executing BD will then figure out what to do with the order, also known as “working the order”.

Retail orders

In general, retail BDs, such as Robinhood, E-Trade, Charles Schwab, etc., typically do not know how to work an order. They are, for the most part, glorified UI+app+accounting. When you send in an order to a retail BD, they will route the order to a specialized BD, also called a WMM, not to be confused with a regular MM — though most WMM’s are also regular MMs, in some capacity (i.e: some instrument+exchange pairs). There are 3 major WMMs in the US – Citadel Securities, Two Sigma Securities and Virtu Financial. There are also a bunch of minor WMMs in the US, but they have very little flow compared to the big 3.

So, when JoeRetail sends an order to RetailBroker, RetailBroker will send the order to WholesaleMarketMaker, who then has 4 choices:

Trade against the order, using their own portfolio.
- There are a bunch of rules they have to comply with, enforced by the SEC/FINRA, to ensure that the WMM gives JoeRetail a reasonable deal.
Forward the order to a dark pool or lit exchange or another BD.
Hold the order on its books.
Cross the order against another order already on its books.
- Must comply with all the rules mentioned above relating to order execution.

From worst to best for JoeRetail:

In general, the first option is usually a bad deal for JoeRetail — because the WMM is informed, while JoeRetail is almost definitely uninformed — there is an information asymmetry and generally speaking, the WMM will come out of the deal better off.
Routing to a dark pool is generally bad for the order as well, for similar reasons.
Being held on the WMM’s books is sort of bad — it implies the order is not immediately executable (it does not cross the far price, which is the best bid for a sell order, or the best ask for a buy order), so the WMM is putting it on ice until something changes and the WMM can decide again later.
Routing to another BD just repeats the process.
Immediately crossing against an order already on the WMM books is OK, but not the best thing.
Routing to an exchange is probably the best thing that can happen to the order.

National best guess for bid and offer

Why is it not the best thing for the order to trade against other client orders on the WMM’s books? Surely those orders must also be uninformed?
Yes, those orders are uninformed, but the problem is that NBBO is weird.

Remember that WMM has to execute within NBBO. But NBBO is not the best bid/offer of all exchanges (it’s just called that). It is just the best protected and lit bid/offer.

For example, if the absolute 2 best offers on all lit exchanges are:
Sell 99 GOOG @ $100
Sell 100 GOOG @ $101

The first order (@ $100) is not the NBBO — because it is an odd lot. So, even though the WMM knows about that order (lit exchange books are public), and you only want to buy 99 GOOG, the WMM does not have to execute your trade at $100, it can execute your buy order at $101. However, if your order to buy 99 GOOG was routed to the exchange, it’ll definitely be executed at $100.

More interestingly, and this is something that most people don’t appreciate — the WMM may not be allowed to fill your buy order @ $100, even if it wants to. For example, if NASDAQ has both those sell orders, and NYSE has this buy order:
Buy 100 GOOG @ $100.10

Then the NBBO is $100.10 to $101. Which means filling your order at $100 will be below the $100.10 best bid, which is against the NMS rule. This situation is known as a crossed market. It happens, but rarely and usually not for very long.

Another problem with NBBO is that it is not well defined. Remember that all the exchanges are located at different geographic locations. So, depending on where you are, market data (i.e: the book) of different exchanges will reach you at different times.

So even if you use the exact same algorithm to build the NBBO, someone in Kentucky and someone in Connecticut can genuinely see different NBBOs, simply because the exchanges’ market data reach them at different times.

Because of all these issues, BDs cannot just use any NBBO algorithm. The algorithm they use must be blessed by the SEC/FINRA. OR, they can just use the SIP. The SIP is a company that publishes various market data for all participants. Because it is sanctioned by the SEC/FINRA, if you use the NBBO published by the SIP, you’ll generally be fine — SEC/FINRA generally won’t give you grief about that.

But that introduces 3 other problems:

The SIP itself is located at some location, which means it’s seeing market data of a certain latency.
The SIP itself has very little incentives to get better (since it’s effectively a mandated monopoly), so it’s software is very slow compared to the rest of the market. It’s common for the SIP to send out data that’s 1-100ms behind what the rest of the market actually see.
Depending on where you are in relation to the SIP source, you may get data that’s even slower because now the data source is 2 hops away.

Finally, the last bad thing about NBBO is that it doesn’t account for hidden orders. We already know the NBBO ignores odd lots. But it also is ignorant of hidden orders. Venues (lit or otherwise) typically allow orders to be hidden from the public and not published in market data. These are typically orders that are big, because if someone wants to sell 1,000,000 shares of GOOG in a single order, anyone seeing that order will freak out and dump GOOG (OMG! They know something we don’t!). To avoid market panic, these large orders are typically hidden — sometimes totally hidden, sometimes they may show up as only 100 shares on the books of the exchanges. That’s why even if you see NBBO as $100 – $101, and you send an order to an exchange to buy at $100.50, you may actually hit a hidden order, and get executed.

Of course, because these orders are hidden, they don’t show up in NBBO, which means WMMs don’t have to honor that $100.50, even if they can reasonably guess that the order is there (there are ways to forecast/predict this, I won’t go into that).

To conclude, by not going to an exchange, you potentially lose out on potential liquidity that can fill your order at a better price. WMMs can, perfectly legally (and sometimes forced to by SEC rules), fill your order against their own portfolio, then go out and buy/sell at a better price on the lit exchange to make an instant profit.

Footnotes

Yes, yes, yes, the terms sound disparaging. They are not meant to be — these are official (and technical) terms. If you don’t like it, talk to the textbooks.

Investing vs Speculating 3

by jankythoughts2April 12, 2021November 2, 20211 Comment

Foreword

I want to start by noting that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, via some formal classes, but mostly self-taught.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

This post is a continuation of Investing vs Speculating and Investing vs Speculating 2. If you have not read those posts yet, you probably should before continuing here. A separate related post, Zero Sum Game, finally rounds up why understanding investing vs speculating is important.

Starting to invest

Whenever someone asks me for newbie investment advice, I almost always tell them the same things:

Read “The Intelligent Investor: The Definitive Book on Value Investing“.
- It is outdated, but contains a lot of still useful information.
Then chase down all the bits that seem wrong/outdated, and in doing that research, hopefully you’ll understand the topics better, and more importantly, understand yourself better.
Finally, you need to decide what kind of person you are.
- Are you an investor? If so, which kind?
- Are you a speculator? If so, which strategy appeals to you more?

Only then, can any sort of useful advice be given.

This is also why whenever you open a brokerage account, the broker always asks you whether you are “hedging, seeking income, seeking growth, etc.”.

Essentially, they are trying to understand which of the above modes apply to you best, and when. And in so doing, they can better tailor their recommendations and advice for you.

I are investor

Not everyone is suited to be an investor.

Some people simply cannot stomach the paper losses that investing sometimes entails. It takes a special kind of crazy, masochistic instinct for someone to look at your portfolio which is down 50%, and think, “OMG, I MUST BUY MORE!“

If you are unable to stomach such losses, and you are also terrible at speculating, then I suggest buying illiquid assets, or simply don’t look at the stock markets at all, after you do your research and have bought.

I won’t lie — doing this is dangerous! You may miss when fundamentals really do change and your model needs updating.

But it’s better than constantly panicking at the slightest dip. If nothing else, you’ll sleep better.

I value value investing

If you are value investing, you typically put in a lot of work per company, which means you likely won’t have time to invest in too many companies. As such, diversification is rare in value investing (remember Buffett’s quote about being “too diversified”).

On the other hand, if you are macro/passive investing, you mostly only consider macroeconomic issues and/or your personal temperament and needs, both of which apply to large swaths (or even all) of companies. As such, diversification helps to dilute the idiosyncratic risks of investing in individual companies.

These are not black/white extremes, it is a spectrum. The more you are willing to dive into the details of companies, the less you should diversify — the more you are sure of a company, the more you should concentrate your bet. The less you are willing to dive into individual companies, the more you should diversify to avoid idiosyncratic risks that you’ve overlooked.

I R speculator

If you are speculating, then there is always the element of “what if you’re wrong”. Combined with the lack of a fallback in terms of earnings, a wrong bet can be disastrous.

As such, successful speculators generally employ very robust risk models, where they:

Limit exposure to each bet (i.e: position sizing)
Limit increasing exposure as the bet works (i.e: take profits if the bet works out well)
Limit downside risk (i.e: cut losses if the bet is souring)

Yes, it seems like everything says “don’t bet”, that’s not quite true. It’s a matter of degree, and depending on your strategy (momentum, mean reversion, event driven or arbitrage), one or another of the 3 factors dominate.

For example, if you are betting on momentum, you typically use small bets on many names. When momentum bets pay off, they tend to pay off big, so even small bets will make a meaningful difference to your entire portfolio. At the same time, you cast a wide net, because you want to ensure that you catch at least a few of the momentum runs.

In momentum bets, limiting downside risk is generally easy — at some point, your momentum model will tell you that momentum is in the opposite direction, which is when you close out the position and/or go short.

But taking profits on the upside is generally hard — typical momentum models will suggest you buy more as the stock rises, because it has more momentum! So (b) is where your risk model should concentrate, for momentum models.

For mean reversion models, the opposite is true — as the stock goes up, your model will naturally tell you to start shorting, while as the stock tanks more, your model will tell you to buy more, potentially catching a falling knife. So for mean reversion, your risk model should concentrate on (c).

Risk models should be crafted carefully with an understanding of the primary model.

Stay true

Whatever you choose to do, be honest with yourself, and be very clear:

What you are doing
How you will make a profit
When you should reevaluate and/or cut losses

If you invest blindly without understanding what you are investing in, you are not even speculating — you are purely gambling.

If you speculate blindly without understanding your exit criteria, you are also just gambling.

Gambling is fine, I have nothing against gambling — but understand that when you gamble, you are paying a fee to be entertained. So gamble if you want, just don’t expect a (positive) return.

Investing vs Speculating 2

by jankythoughts2April 12, 2021July 24, 2021Leave a comment

Foreword

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

This post is a continuation of Investing vs Speculating, and if you have not read that yet, you probably should before continuing here. There is also a final wrap up to this series, Investing vs Speculation 3. Finally, a separate related post Zero Sum Game rounds up why understanding investing vs speculating is important.

Question

What do you do if the market tanks 50% tomorrow?
The answer, as always, is, “it depends”.

To formulate a proper answer, we first need to discuss why people buy financial assets, because the reason why they buy financial assets is key to understanding their mindset and motives.

Why buy assets

The two main reasons to buy financial assets are: investing and speculating.
I want to note that I have nothing against investing nor speculating. Both are, in my opinion, critical for the proper functioning of markets. Therefore, read the following with the understanding that I’m not disparaging either, but just noting their characteristics.

Investing

There are 3 main types of investing: value investing, macro investing and passive investing.

Value investing, where

You look deeply at the fundamentals of the company’s business,
and try to formulate some sort of projection/model for the path the business will take.
Based on your understanding of the risks and characteristics of the business, you then decide what kind of returns you would accept.
Based on the returns you would accept, you can then estimate a price which you would be willing to pay.
Finally, you buy stock in the company if it is trading for lower than what you’d be willing to pay. Otherwise, you move on to the next company to evaluate.

For example,
Let’s say I believe StableCo will generate around $100 per year for the next 10 years. StableCo is in a stable industry, so the business is unlikely to grow much, but is also unlikely to decline significantly. Therefore, there’s probably little variance to that $100 earnings that I should expect.

For such a company, I decide that I want at least 7% return per year. That translates to a total market cap of around $1429. That is, I would be willing to buy the whole of StableCo for $1429. If StableCo had 100 shares outstanding, then I would be willing to pay $14.29 per share.

Note: There are various definitions of “value investing”, some of which are really more a form of speculation using quantitative methods. Here, I am referring to the definition of “value investing” as popularized by Benjamin Graham, and that which is espoused by his book “The Intelligent Investor”.

Macro investing, where

You are focused more on the macroeconomics side of things.
You form models/projections on how different economies and/or sectors of an economy will perform in the near future,
and you allocate resources to those which you believe will perform relatively better.

For example,
I analyzed the political, economical and financial policies of two countries, Wakanda and Rohan. Based on my understanding of these policies, and the geographic realities of each country, I’ve decided that:

Wakanda would be able to commercialize their natural resources. That stream of revenue would allow the government to dramatically improve the lives of its citizens, achieving an annual growth of 10% of its economy.
Rohan, however, has an economy that’s effectively stuck in the medieval age. Its infrastructure is essentially a series of dirt tracks for horse drawn buggies, and there is little chance its economy will grow by more than 2-3% a year.

Because of these, I decide to allocate my portfolio entirely to Wakanda. Within Wakanda, I further subdivide my portfolio, so that a majority of the portfolio is in industries related to the extraction and export of natural resources.

Passive investing, where

You assume, a priori, that the economy generally trends upwards,
and so if you buy a bunch of different companies, you’ll be able to diversify away idiosyncratic risk.
This then allows you to just make whatever returns the economy provides.

Note that there is significant overlap between passive investing and macro investing. In both, you generally decide on a portfolio allocation at the macro level — domestic economy vs international economies, diversification across sectors, etc.

The main difference, is that in passive investing, you generally don’t form an opinion of how each will perform against the other. Instead, you base your portfolio allocation based on your risk tolerances and other needs.

Answer for investors

As mentioned in Investing vs Speculating, in all cases, your goal is to earn the returns of the businesses that the companies you bought are engaging in.

When you are purely investing, you should buy whenever you feel that the future earnings of the companies you are buying will provide sufficient return for the current prices you are paying today. As such, the future prices of the companies don’t really matter — what matters is the current prices you are paying now vs the future earnings of the companies.

If you are purely investing, and the stock price of the company you’ve bought tanks by 50%, then you should:

Determine if the fundamental characteristics of the business of the company has changed.
If not (i.e: your prior model is still accurate), you should either:
1. Ignore the stock price — after all, you are not looking to earn your return from the stock price, OR
2. Determine if the new stock price is low enough that you can risk putting more money into the company.
  - Remember that putting more money down in the same asset means increasing your risk to that asset, so you’ll need a larger margin of error to compensate for that risk.
If yes (i.e: the fundamentals of the company has changed), you should rebuild your model/projection for the company, then:
1. Sell the stock if the new projection suggests that at the new stock price, you would not be making the return you are looking for, OR
2. Ignore the stock price, if in the new model, the new stock price justifies the current investment in that company, OR,
3. Buy more stock, if in the new model, the new stock price provides enough margin of error to compensate for the additional risk.

Speculating

There are 4 main types of speculation: momentum, mean reversion, event driven and correlation.

For simplicity, I’ll just assume we are buying. Shorting is just the inverse, and should be fairly easy to reason out.

Momentum is where you expect whatever has gone up in the near past, will continue going up in the near future.

For example,
It has been shown that most stocks show some form of momentum — if a stock has gone up in the recent past, it tends to go up more in the near future.

A simple momentum strategy would be to just buy any stock whose price is above its 50day moving average, and hold them for 1 week. (1)

Mean reversion is where you expect whatever has gone down in the near past, will go up in the near future.

For example,
Over long periods of time, the VIX index tends to revert to a range of around 10-20.

A simple mean reversion strategy here would be to just short the VIX index whenever it is above 80, until it goes below 30. (2)

Event driven is where you expect some event in the near future will cause the asset to go up.

For example,
LargeBuyerCo has announced that it is looking to acquire some companies to expand on its online advertising platform.

You did some research and narrow down the list of candidates to 3 companies which are publicly traded. You buy the stocks of each 3 company, and wait for LargeBuyerCo to announce their targets. (1)

Correlation is where you expect two related time series to exhibit similar performance over time.

For example,
The countries of Gondor and Arnor are close to each other geographically, and share many characteristics such as political climate, monetary and fiscal policies, etc. The citizens of both countries can also move freely between the both countries, and so, each country is the largest trading partner of the other.

Based on these factors, you expect that economies of Gondor and Arnor to be closely linked. You therefore build 2 baskets of stocks — one holding the largest 10 companies in Gondor, and the other building the largest 10 companies of Arnor.

You expect that these 2 baskets of stocks will move very similarly to each other over time, and so whenever one basket is underperforming, you buy that basket and short the other. You do so until the gap between the performance closes, which is when you close your position. (1)

Answer for speculators

As mentioned in Investing vs Speculating, in all cases, your goal is to earn a profit by someone paying more for the asset when you sell it to them.

There are 2 main ways for the value of the asset to go up — either the fundamentals become better (i.e: the asset is fundamentally worth more), or the price multiple becomes higher (i.e: the asset is priced richer).

Note that while we are looking at fundamentals in the first case, we aren’t “investing”! We are betting that the fundamentals will improve, and we are looking to profit from the increase in the price of the asset when the fundamentals improve, not from the earnings of the businesses because of the same fundamental improvement.

Another name for the second case is the “Greater Fool theory”. Essentially, you buy an asset without an understanding of whether the fundamentals justify the price, but with the belief that someone else will pay a richer price in the near future.

Examples of where fundamentals may change:

New product line (e.g: new iPad model)
Changes in characteristics of the industry (e.g: lithium mining after EVs become popular)
Inflation (e.g: devaluation of currency)
Reduced regulations (e.g: more opportunities to squeeze out profits)
Cyclical industry at trough (e.g: industry wide recent underinvestment due to prior overinvestment)

Examples of where price multiples may change:

Price insensitive buyer (e.g: buybacks, index inclusion)
Reduction in risk free rate (i.e: reduced discounting of future earnings)
General market euphoria/fear (e.g: when a bubble is forming, all stocks tend to do well)

So, what should you do, if the stock of the company you purely speculated in tanks 50%?

If you are betting on momentum, then clearly you were wrong, and you should close the position, and maybe even go short instead.
If you are betting on mean reversion, then either you were wrong, or you were early.
Trying to figure out which is generally hard, and requires looking deeper at your model and figuring out what went wrong.
1. If you believe your model to still be correct, you either hold on the position, or buy more.
2. If you believe your model was wrong, then you close out the position, and rework your model.
If you are betting on an event,
1. If the drop was after the event, then clearly you were wrong and you should close out the position.
2. If the event has not occurred, you need to decide if your model of whether the event will still occur, and what that event entails for the stock price is still accurate.
  1. If so, you should probably hold, and/or buy more.
  2. Otherwise, you should close the position.
If you are trying to trade correlations, then the other leg(s) of your trade should have mitigated the bulk of the 50% drawdown.
1. If not, your model may be wrong, and you should think carefully to see if perhaps you missed something, or if situations have changed, so that the model no longer works.

Wrapping up

Obviously, there is a lot of overlap between all the above. While for the most part, whether an action is more investing or more speculating is generally obvious, there is also a lot of grey area.

Realistically, very few people purely invest, and very few people purely speculate — it’s mostly a matter of degree.

In some cases, people deceive themselves — they started out trying to speculate, but when the trade went wrong, cognitive dissonance convinces them that they were actually investing, and so they hold on to a bad trade far longer than they should.

In the end, they end up hurting only themselves.

In yet other cases, people start out speculating, but the success of the trade triggers their greed and they convince themselves they had an investment thesis all along. They too, then, hold on for far too long.

If enough people do this to the same asset, a bubble forms, and for a while (which can be a very long time), everyone can seem to be really smart. Famous bubbles in the past have lasted years… before reality rudely intrudes and everything comes crashing down.

Sometimes flip flopping between investing and speculating is bad, but sometimes it is good. If you do flip flop, then you should be sure to be very clear to yourself why you are flip flopping.

If you changed a speculative bet into an investment, you should be very clear and very sure about the model you are using, and be sure that the projected returns is at or above your desired return. You should evaluate everything from scratch, as if it was a new investment.

Otherwise, you stand a fairly good chance of blinding yourself if the stock price deteriorates, by constantly convincing yourself that “you are investing and price does not really matter”.

Footnotes

This is an example, not an actual, viable strategy.
Shorting is inherently dangerous, and shorting a volatile index like the VIX is doubly so. The short VIX strategy is an example, not an actual, viable strategy.

Investing vs Speculating

by jankythoughts2April 12, 2021July 24, 2021Leave a comment

Foreword

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

This post is the first of 3, and is meant to lay the groundwork for the following posts: Investing vs Speculating 2 and Investing vs Speculating 3. A separate related post Zero Sum Game rounds up why understanding investing vs speculating is important.

Definitions

I personally prefer the traditional/classical definition of investing vs speculating, which is roughly:

Investing – The act of putting money to use, by purchasing some productive asset, and then profiting from the products of that asset. For example, by buying a business with a factory, and then producing Widgets (the product) which can then be sold by the business for a profit.

Speculating – The act of buying and selling assets with the intention of profiting from the appreciation in prices of the assets. For example, by buying the same business above, and then selling the business (not Widget!) again to someone else at a higher price.

For some, these definitions may seem foreign — for anyone who started managing money around the late 90’s, their personal definition of “investing” may be closer to my definition of “speculating”, or at least, a mix of both. And they probably define “speculating” as something along the lines of “investing with high risk”.

That’s fine! You are certainly allowed to define words as you see fit, within reason. But I feel that while we are on the topic of finance, we should probably use definitions from finance. This avoids ambiguity, since different people reasonably can have slightly different preferences on definitions.

Hopefully in the following post and future posts, this differentiation and the reason for it, will become clearer.

PredictableCo

Let’s say everyone in the world has a crystal ball, and can see for a company, PredictableCo, how much profits it’ll make before PredictableCo does out of business sometime in the future. How PredictableCo ends doesn’t matter, but let’s just say it goes bankrupt (i.e: stock is worth $0) (1).

Now, the crystal ball is mission specific, and only allows you to see the future profits of PredictableCo, and nothing else. Specifically, you do not know future interest rates, just current and past interest rates.

So, given this, how much should PredictableCo be worth now?

The answer should be trivial — PredictableCo’s future profits are essentially “risk free” (because crystal balls are like boy scouts — they never lie). So, take all pending future earnings, discount to present using the relevant “expected future interest rates”, and that’s your price for PredictableCo.

However “expected future interest rates” are, themselves, speculative — nobody knows what they’ll be (crystal balls for future interest rates is a developing feature). Right now, there’s just a bunch of assumptions and predictions for them. So, if person A assumes future interest rates will be higher, they may be willing to pay less for PredictableCo than person B who assumes future interest rates to be lower.

That said, we can make this statement, which I believe will be true:

The net amount of gains and losses, from all investors of PredictableCo, across all time, based only on PredictableCo, will be exactly equal in dollar value to the sum of all earnings of PredictableCo.

As a simple example, let’s say PredictableCo generates $100 a year for 10 years and then goes bankrupt. The exact way this $100 is returned to the owner is mostly irrelevant for this discussion, but let’s say this is paid out yearly as dividends.
Total earnings = $1,000.

Let’s say I create PredictableCo from nothing in year 1.
Year 1:
I make $100 from the business.

And then I sell PredictableCo to B for $500 in year 2.
Year 2:
I get $500 from B.
B pays $500 to me, makes $100 from the business.
Net for me: (100)+(500) = $600.

In year 4, B sells PredictableCo to C for $200.
Year 3:
B makes $100 from the business.

Year 4:
B gets $200 from C.
C pays $200 to B, makes $100 from the business.
Net for B: (-500+100)+(100)+(200) = -$100

C then holds PredictableCo until year 10 when it ceases to exist.
Years 5-10:
C makes $100 each, total $600 from the business.
Net for C: (-200+100)+600 = $500

Net for everyone = $600(me) – $100(B) + $500(C) = $1,000 = total earnings of PredictableCo

To put it simply, the net amount of absolute dollars that everyone makes from a single company, simply from trading/investing/speculating on that company, is just the sum of all earnings from that company (2).

Investing vs Speculating

And if you think about it, it really doesn’t matter if you know or do not know what the company’s future earnings will be. The statement still holds. The only thing that changes, if you cannot predict future earnings, is that the price people are willing to trade that company for is more volatile, because different people naturally have different expectations, same as how they have different expectations for interest rates in our crystal ball model.

And therein lies my mental model of investing vs speculating. When I’m investing, I’m making a prediction of the future earnings, with the expectation that I’ll get those future earnings one way or another (dividends, liquidation, stock price increase, etc.). The exact method that the earnings is received doesn’t really matter, and importantly, some of these methods (such as stock price increases) may incorporate speculative profits/losses from others.

When I’m speculating, I’m making a prediction of other people’s predictions. When I buy for speculation, I’m predicting that other people predict the company will be worth more, regardless of whether it’s because they are investors (and thus predict more earnings than the current price indicates) or speculators (and thus predict that yet other people predict an even higher price).

If you are investing, you need to figure out the fundamentals of that company. You need to know what the earnings are, whether they are sustainable, whether the company is sustainable, etc. And then you need to make a guess on the future interest rates, and finally discount everything to present. If you can buy the company for a better price than your result, you should (3). Otherwise, you shouldn’t.

So think about your own “investment process”, as well as the process of people you listen to for investment advice. Are you/they doing these? Are you/they investing or speculating?

I have nothing against speculation — I do it myself all the time, and I believe it is an important component of a fully functioning market.

But there is a dramatically different mindset when you are investing vs when you are speculating.

Don’t conflate the two for an instant, or you may end up confusing or lying to yourself, to detrimental results.

Footnotes

In the event that PredictableCo gets bought out instead of going bankrupt, you can model it this way:
- 1s before the buyout, PredictableCo makes a profit of exactly the amount of the buyout, by selling all its assets, and paying off all its debts.
- 1s after that, PredictableCo, because it no longer has assets nor debts, goes bankrupt at $0.
We are ignoring fraud, taxes, etc. You can model fraud, taxes, etc. as basically just a reduction in earnings.
Note that in this case, “earnings” is individualized and should include opportunity costs. If you don’t, then the statement should be reworded to:
You should buy the companies that are the most undervalued.